Flashback Foreword: Supervised Risk Predictor of Breast Cancer
Authors: Davide Soldato, Kathy D. Miller
Journal: Journal of Clinical Oncology (2023)

Article Tools FLASHBACK FOREWORD Article Tools OPTIONS & TOOLS Export Citation Track Citation Add To Favorites Rights & Permissions COMPANION ARTICLES JCO Flashback: An Intrinsic Subtype-Based Risk Prediction Model for Early-Stage Breast Cancer (2009). September 06, 2023 Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes. September 06, 2023 ARTICLE CITATION DOI: 10.1200/JCO.22.02927 Journal of Clinical Oncology - published online before print September 6, 2023 PMID: 37672880 Flashback Foreword: Supervised Risk Predictor of Breast Cancer Davide Soldato , MD1,2xDavide SoldatoSearch for articles by this author and Kathy D. Miller , MD3,4xKathy D. MillerSearch for articles by this author Show More 1ASCO Editorial Fellow, Journal of Clinical Oncology, Alexandria, VA2Cancer Survivorship Group, INSERM Unit 981, Gustave Roussy, Villejuif, France3Senior Deputy Editor, Journal of Clinical Oncology, Alexandria, VA4Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN https://doi.org/10.1200/JCO.22.02927 First Page Full Text PDF Figures and Tables © 2023 by American Society of Clinical OncologyTHE TAKEAWAYIn 2009, Parker et al1 described a molecular classification of early-stage breast cancer using gene expression data to identify the four intrinsic subtypes termed luminal A, luminal B, human epidermal growth factor receptor 2–enriched, and basal-like, with vastly different prognosis and response to therapy. Although the resulting assay has had little impact on clinical care, this work paved the way for pivotal translational research toward personalizing breast cancer therapy.AUTHOR CONTRIBUTIONSConception and design: All authorsManuscript writing: All authorsFinal approval of manuscript: All authorsAccountable for all aspects of the work: All authorsAUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTERESTFlashback Foreword: Supervised Risk Predictor of Breast CancerThe following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/jco/authors/author-center.Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments).Davide SoldatoHonoraria: AstraZenecaTravel, Accommodations, Expenses: NovartisKathy D. Miller This author is a Senior Deputy Editor for Journal of Clinical Oncology. Journal policy recused the author from having any role in the peer review of this manuscript.Consulting or Advisory Role: Merck, Genentech/Roche, AstraZeneca, Bristol Myers Squibb/Celgene, CelcuityResearch Funding: Pfizer (Inst), Astex Pharmaceuticals (Inst), British Biotech (Inst), CytomX Therapeutics (Inst), alphamab (Inst)No other potential conflicts of interest were reported. Companion JCO Flashback: An Intrinsic Subtype-Based Risk Prediction Model for Early-Stage Breast Cancer (2009) Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes